Security is a concern in a variety of transactions involving private information. Iris recognition is a well-accepted and accurate means of biometric identification used in government and commercial systems around the world that enables secure transactions and an added layer of security beyond keys and/or passwords. Due to the increased security provided by iris recognition systems, an increase in use of such systems has occurred around the world.
As biometric identification increases in use, attacks on systems that use biometrics for security may also increase resulting in a greater demand for anti-spoofing measures. In particular, the security of such systems can be threatened by presentation of spoof attacks (attacks that present the biometric system with facsimiles of the real biometric credentials in an attempt to defraud the biometric system). Banks, hospitals, schools, stores, businesses, military installations, and other government and/or commercial systems could benefit from biometric security that is hardened against spoofing attacks.
Those looking to defraud iris recognition systems generally attempt to use a wide variety of attacks. In the presentation attack, the defrauder can present a fraudulent, non-live iris in place of a live biometric organ to the recognition system. For example, the defrauder can present a picture of an iris in place of a real iris. The fraudulent iris can be so realistic in every aspect that the iris recognition system can mistake it for a real iris that is enrolled in the system, mistakenly verifying its identity and granting the defrauder access to the otherwise protected system. The defeat of iris biometrics using simple image-based spoofing could tarnish the reputation of iris biometrics.
There are many systems for anti-spoofing or liveness detection in biometrics. To defend against presentation attacks, biometric systems identify inconsistencies in the presentation of false biometric credentials. There are many existing techniques for differentiating a live biometric sample (e.g., face, iris, or the like) from a facsimile (e.g., printed paper, computer monitor, tablet display, sculpted face, fake eyeball, or the like). Iris recognition systems that test liveness of a presented iris can use methods including pupillometry, active gaze and blink detection, and complex systems of infrared signaling.
In pupillometry, a stimulus (such as a bright visible light) causes a subject's pupil to contract in real time, indicating liveness. Detection of saccadic motion of the eye also provides an indication of liveness of the subject. A picture of an iris or a fake eyeball with printed iris texture would not respond to bright light with pupilary contraction as would a live iris. In such cases, the stimulus of a bright light would distinguish a live iris from the static picture or model of an iris and would therefore defend against a false presentation in a system that could provide the relevant stimulus and measure the response. The stimulus light is considered obtrusive by some users. In addition, pupillometry systems may need extra time to operate, thereby slowing the time for identification.
Additional existing techniques for differentiating a live biometric sample from a facsimile compare specular reflections from the cornea, detect an absence of tell-tale reflections, or involve stereo imaging. Stereo imaging or time-of-flight depth sensors can also indicate a presentation attack by differentiating a flat or bent paper image from a realistic three-dimensional relief of an actual face. Stereo imaging generally requires stereo reconstruction algorithms to produce the three-dimensional imagery to analyze the presented face. As new anti-spoofing techniques are developed, attackers attempt to create facsimiles that can defeat these new anti-spoofing measures.
Thus, a need exists for improved biometric analysis systems including anti-spoofing to ensure the security of transactions and make presentation attacks more difficult. These and other needs are addressed by the systems and methods of biometric analysis of the present disclosure.